Mesh network services for devices supporting dynamic direction information

ABSTRACT

With the addition of directional information in the environment, a variety of service(s) can be provided on top of user identification or interaction with specific object(s) of interest. For instance, a user can opt into a mesh network and leverage services available via the mesh network. The user can also contribute to knowledge within the mesh network by allowing for information related to the user to be aggregated and employed by others, e.g., targeted provisioning of services. The interaction with the mesh network can occur passively (e.g., as a background application not generally visible to the user), or actively where for example the user can initiate collecting or logging of information from/to the mesh network.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Application Ser.No. 61/074,415, filed on Jun. 20, 2008, entitled “MOBILE COMPUTINGSERVICES BASED ON DEVICES WITH DYNAMIC DIRECTION INFORMATION,” and U.S.Provisional Application Ser. No. 61/074,590, filed on Jun. 20, 2008,entitled “MOBILE COMPUTING SERVICES BASED ON DEVICES WITH DYNAMICDIRECTION INFORMATION”, the entireties of which are incorporated hereinby reference.

TECHNICAL FIELD

The subject disclosure relates to provision of direction-based servicesbased on direction information and/or other information, such aslocation information, of a device, and to opting into mesh network(s)and related services that leverage information gathered from multipledevices supporting the direction-based services.

BACKGROUND

By way of background concerning some conventional systems, mobiledevices, such as portable laptops, PDAs, mobile phones, navigationdevices, and the like have been equipped with location based services,such as global positioning system (GPS) systems, WiFi, cell towertriangulation, etc. that can determine and record a position of mobiledevices. For instance, GPS systems use triangulation of signals receivedfrom various satellites placed in orbit around Earth to determine deviceposition. A variety of map-based services have emerged from inclusion ofsuch location based systems that help users of these devices to be foundon a map, and to facilitate point to point navigation in real-time andsearch for locations near a point on a map.

However, such navigation and search scenarios are currently limited todisplaying relatively static information about endpoints and navigationroutes. While some of these devices with location based navigation orsearch capabilities allow update of the bulk data representing endpointinformation via a network, e.g., when connected to a networked portablecomputer (PC) or laptop, such data again becomes fixed in time.Accordingly, it would be desirable to provide a set of richerexperiences for users than conventional experiences predicated onlocation and conventional processing of static bulk data representingpotential endpoints of interest.

The above-described deficiencies of today's location based systems anddevices are merely intended to provide an overview of some of theproblems of conventional systems, and are not intended to be exhaustive.Other problems with the state of the art and corresponding benefits ofsome of the various non-limiting embodiments may become further apparentupon review of the following detailed description.

SUMMARY

A simplified summary is provided herein to help enable a basic orgeneral understanding of various aspects of exemplary, non-limitingembodiments that follow in the more detailed description and theaccompanying drawings. This summary is not intended, however, as anextensive or exhaustive overview. Instead, the sole purpose of thissummary is to present some concepts related to some exemplarynon-limiting embodiments in a simplified form as a prelude to the moredetailed description of the various embodiments that follow.

Direction based pointing services are provided for portable devices ormobile endpoints. Mobile endpoints can include a positional componentfor receiving positional information as a function of location of theportable electronic device, a directional component that outputsdirection information as a function of an orientation of the portableelectronic device and a processing engine that processes the positionalinformation and the direction information to determine a subset ofpoints of interest relative to the portable electronic device as afunction of the positional information and/or the direction information.

Devices or endpoints can include compass(es), e.g., magnetic orgyroscopic, to determine a direction, and location based systems fordetermining location, e.g., GPS. To supplement the positionalinformation and/or the direction information, devices or endpoints canalso include component(s) for determining speed and/or accelerationinformation for processing by the engine, e.g., to aid in determinationof gestures made with the device.

With the addition of directional information in the environment, avariety of service(s) can be provided on top of user identification orinteraction with specific object(s) of interest. For instance, a usercan opt into a mesh network and leverage services available via the meshnetwork. The user can also contribute to knowledge within the meshnetwork by allowing for information related to the user to be aggregatedand employed by others, e.g., targeted provisioning of services. Theinteraction with the mesh network can occur passively (e.g., as abackground application not generally visible to the user), or activelywhere for example the user can initiate collecting or logging ofinformation from/to the mesh network.

An aspect of the claimed subject matter relates to optimizing the meshnetwork and interaction therewith so as to facilitate provisioning ofservices. User and/or device data can be collected and mined inconnection with improving services provisioned to users/devices. Forexample, demographic information can be collected and correlated withactions taken as well as extrinsic evidence (e.g., weather, time of day,user or device context, state of user or device, holidays, weekendversus business day, path of navigation, . . . ) to map preferencesamong like users or devices. Accordingly, such mapping can be leveragedto provision targeted services to users or devices within the meshnetwork. Suggestions regarding products or services based on the dataaggregation and/or mappings can be improved. Automated actions can betaken based on a utility-based analysis, e.g., a cost benefit analysiswhere the benefit associated with a particular automated action with agiven confidence level outweighs the cost of taking an incorrect orundesired action.

These and other embodiments are described in more detail below.

BRIEF DESCRIPTION OF THE DRAWINGS

Various non-limiting embodiments are further described with reference tothe accompanying drawings in which:

FIGS. 1 and 2 are block diagrams of non-limiting architectures for meshnetwork interaction systems in accordance with one or more embodiments;

FIG. 3 is a flow diagram of a non-limiting process for data collectionin connection with a mesh network;

FIG. 4 is a flow diagram of a non-limiting process for data processingin connection with a mesh network;

FIGS. 5 and 6 are flow diagrams of non-limiting processes for service(s)provisioning in connection with a mesh network;

FIG. 7 is a flow diagram of a non-limiting process for targetedadvertisement provisioning in connection with a mesh network;

FIG. 8 is a flow diagram of a non-limiting process for advertisementpricing in connection with a mesh network;

FIG. 9 is a flow diagram of a non-limiting process for modification ofservices provisioning in connection with a mesh network;

FIG. 10 is a flow diagram of a non-limiting process for data collectionand filtering across multiple devices in connection with a mesh network;

FIG. 11 is a flow diagram of a non-limiting process for matching userswith services in connection with a mesh network;

FIGS. 12 and 13 are flow diagrams of non-limiting processes for servicesprovisioning in connection with a mesh network;

FIG. 14 is a flow diagram of a non-limiting process for marking pointsof interest for later interaction;

FIG. 15 is a flow diagram of a non-limiting process for designatingpoints of interest for later interaction;

FIG. 16 is a block diagram of a device illustrating a specific apparatusfor marking points of interest for delayed interaction in connectionwith direction based services;

FIG. 17 is a flow diagram of a non-limiting process for designatingpoints of interest associated with a given place for later interaction;

FIG. 18 is a block diagram of an exemplary device architecture fordevice that supports direction based services in accordance with one ormore embodiments;

FIG. 19 illustrates an exemplary sequence for delayed interaction withPOIs at a location as a future advertising source;

FIG. 20 is a block diagram illustrating a non-limiting implementation inwhich POIs are scanned based on encoding information;

FIG. 21 is a block diagram illustrating market players in an overalladvertising model established based on interest in satisfying thedelayed interactions defined according to one or more embodimentsherein;

FIG. 22 is a block diagram illustrating a variety of ways in which userintent can be inferred or implied with respect to points of interest;

FIGS. 23 and 24 illustrate representative scenarios where a delayedinteraction facilitates a better timing for a transaction regarding agiven item of interest;

FIG. 25 is a block diagram illustrating the formation of motion vectorsfor use in connection with location based services;

FIG. 26, FIG. 27 and FIG. 28 illustrate aspects of algorithms fordetermining intersection endpoints with a pointing direction of adevice;

FIG. 29 represents a generic user interface for a mobile device forrepresenting points of interest based on pointing information;

FIG. 30 represents some exemplary, non-limiting alternatives for userinterfaces for representing point of interest information;

FIG. 31 represents some exemplary, non-limiting fields or user interfacewindows for displaying static and dynamic information about a givenpoint of interest;

FIG. 32 illustrates a sample overlay user interface for overlaying pointof interest information over a camera view of a mobile device;

FIG. 33 illustrates a process for predicting points of interest andaging out old points of interest in a region-based algorithm;

FIG. 34 illustrates a first process for a device upon receiving alocation and direction event;

FIG. 35 illustrates a second process for a device upon receiving alocation and direction event;

FIG. 36 is a block diagram representing an exemplary non-limitingnetworked environment in which embodiment(s) may be implemented; and

FIG. 37 is a block diagram representing an exemplary non-limitingcomputing system or operating environment in which aspects ofembodiment(s) may be implemented.

DETAILED DESCRIPTION Overview

As discussed in the background, among other things, current locationservices systems and services, e.g., GPS, cell triangulation, P2Plocation service, such as Bluetooth, WiFi, etc., tend to be based onlocation of the device only, and tend to provide static experiences thatare not tailored to a user because the data about endpoints of interestis relatively static, or fixed in time. Another problem is thatexperiences of a single user are by definition limited, and thusservices predicated on information from the single user are limited toscope of that information. In such a system, a user may interact with anumber of different points of interest (POIs), and such user data aboutthe interactions can be stored in a cloud, but as mentioned, not muchcan be inferred from a single user alone.

An aspect of the claimed subject matter provides a way for users to optinto a mesh network, which enables collective data to be integrated intothe application experience. For instance, a single user path based ondirectional vector information recorded from a direction based servicesenabled device does not show much about human behavior, but aggregateuser paths charted over time can indicate a lot about traffic in aroadway, for instance, or peak times to avoid getting coffee at acertain coffee shop. In this respect, most any POI can have statisticaldata about how users interact with it, and applications can be built onthat statistical data to the benefit of mesh users. A variety ofreal-time scenarios are explored where mesh data is used for particularuser beneficial applications.

At least partly in consideration of these deficiencies of conventionallocation based services, various embodiments of a portable device areprovided that collect or provide information from/to the user or devicein connection with employing services associated with the mesh network.A dynamic data aggregation scheme can be employed that builds aknowledge base of the mesh network. Information regarding user or deviceinteraction with the mesh network can be collected, aggregated,analyzed, conditioned, filtered, mined, and the like to improve accuracyof a data model that facilitated provisioning of services associatedwith the mesh network. As noted herein, interaction with the meshnetwork can occur passively (e.g., as a background application notgenerally visible to the user), or actively where for example the usercan initiate collecting or logging of information from/to the meshnetwork. Various incentives can be employed to facilitate gathering ofsuch user or device data. For example, enhanced services, free goods orservices, discounts, tertiary products/services (e.g., free media) canbe offered in exchange for a user or device providing valuable personaldata. Likewise, a point, reward, sharing threshold system or the likecan be employed to encourage contributing to the mesh network knowledgebase.

As a result of building a robust and accurate mesh network servicesmodel, targeted services can be provided that facilitate provisioning ofservices to users or devices within the mesh network. For example,observing user or device interaction within a particular geographicregion, or at certain times of the day can result in learning that usersof a particular demographic profile (e.g., particular age, income level,. . . ) traverse from point A to point B with population density Fduring time range H and have a J probability of responding to a targetedadvertisement for coffee with a confidence level of M where (A, B, F, H,J, and M are variables). Additionally, enhanced filtering schemes can beemployed that prevent nuisance data interruptions from reaching a useror device. It is to be appreciated that information desirable to oneindividual may be a nuisance to another. The above-noted knowledge basecan facilitate provisioning of services so that it enhances a user ordevice experience so that data and type thereof is provided when desiredand useful, and undesired or non-useful information is filtered withhigh confidence level.

An aspect of the claimed subject matter relates to optimizing the meshnetwork and interaction therewith so as to facilitate provisioning ofservices. User and/or device data can be collected and mined inconnection with improving services provisioned to users/devices. Forexample, demographic information can be collected and correlated withactions taken as well as extrinsic evidence (e.g., weather, time of day,user or device context, state of user or device, holidays, weekendversus business day, path of navigation, . . . ) to map preferencesamong like users or devices. Accordingly, such mapping can be leveragedto provision targeted services to users or devices within the meshnetwork. Suggestions regarding products or services based on the dataaggregation and/or mappings can be improved. Automated actions can betaken based on a utility-based analysis, e.g., a cost benefit analysiswhere the benefit associated with a particular automated action with agiven confidence level outweighs the cost of taking an incorrect orundesired action.

While each of the various embodiments herein are presentedindependently, e.g., as part of the sequence of respective Figures, onecan appreciate that a portable device and/or associated networkservices, as described, can incorporate or combine two or more of any ofthe embodiments. Given that each of the various embodiments improve theoverall services ecosystem in which users wish to operate, together asynergy results from combining different benefits. Accordingly, thecombination of different embodiments described below shall be consideredherein to represent a host of further alternate embodiments.

A non-limiting device provisioned for direction based services includesan engine for analyzing location information (e.g., GPS), directioninformation such as compass information (e.g., North, West, South,East), and optionally movement information (e.g., accelerometerinformation) to allow a platform for pointing to and thereby findingobjects of interest in a user's environment. A variety of scenarios arecontemplated based on a user finding information of interest aboutobjects of interests, such as restaurants, or other items around anindividual, or persons, places or events of interest nearby a user andtailoring information to that user (e.g., coupons, advertisements),however at a time later than the finding.

Details of various other exemplary, non-limiting embodiments areprovided below.

Mesh Network Services for Devices Supporting Dynamic DirectionInformation

Referring now to the drawings, with reference initially to FIG. 1,computer-implemented system 100 can aggregate information regarding aset of devices or users interacting with services, devices, individuals,groups, or the like. Generally, system 100 can include provisioningcomponent 102 that can interface with network-accessible data storageservice 104, and facilitate provisioning of targeted services torespective users or devices. Data storage service 104 can facilitatearchival of data associated with customers, clients, devices (e.g., user106) of data storage service 104 as well as retrieval of any sucharchived data 108 by user 106. Moreover, as described in greater detailinfra data storage service 104 can store a knowledge base or data modelwhich can facilitate provisioning of services in accordance withembodiments described herein. The knowledge base or data model can bestored at a single location, in a distributed framework, or a hybrid(e.g., individual knowledge bases or data models can dynamicallyintegrate or interact in a mesh network like fashion). It is to beappreciated that the term “user” can apply to an individual, group,device(s), services or the like. Both archival or retrieval ofarchived/aggregated data 108 are labeled and referred to herein astransactions 110, which can generalize other transactions associatedwith archived/aggregated data 108 as well, such as on-demand conversionor migration requested by user 106 and so forth. Moreover, it should beunderstood that data storage service 104 can be constructed to operateaccording to very particular networking configurations or topologies,which are discussed infra in connection with FIG. 2. Appreciably,provisioning component 102 (as well as other components describedherein) can be configured in a distinct or specific manner based uponthe configuration of data storage service 104.

While still referring to FIG. 1, but turning now also to FIG. 2, diagram200 depicts an example topology to which data storage service 104conforms. In particular, in one or more aspects of the claimed subjectmatter, data storage service 104 can be configured as a distributednetwork and/or a mesh network. Mesh networking is a way to route data,voice and instructions between nodes (also referred to as “peers”). Itallows for continuous connections and reconfiguration around broken orblocked paths by “hopping” from node to node until a destination isreached. A mesh network whose nodes are all connected to each other is afully connected network. Mesh networks differ from other networks inthat the component parts can all connect to each other via multiplehops. As employed herein mesh networks are type(s) of ad hoc network,and the term is intended to include mobile ad hoc networks (MANET) whichprovides for mobility of the nodes.

Mesh networks can be self-healing: the network can still operate evenwhen a node breaks down or a connection goes bad. As a result, such meshnetwork is very reliable. This concept is applicable to wirelessnetworks, wired networks, and software interaction.

More specifically, the mesh or distributed network can include multiplepeers, denoted here as peers 202 ₁-202 _(N), where N can besubstantially any integer. Each peer 202 can be connected to other peers202, by way of any suitable connectivity scheme or architecture such asa wide area network (WAN) or a local area network (LAN), labeled here asWAN/LAN 204. The mesh network can be a full mesh network in which everypeer 202 is connected to all other peers 202. Alternatively, the meshnetwork can be configured according to a partial mesh topology in whichone peer 202 can be connected to all other peers 202, while a secondpeer 202 is connected only to a subset of all other peers 202, typicallyonly the peers 202 in which the second peer 202 communicates with themost or exchanges the most data.

Each peer 202 can represent a node in the mesh network (or anotherdistributed network) and can be physically implemented by a server,workstation, personal computer, laptop, game console, phone, personaldigital assistant (PDA), or substantially any other suitable device.Moreover, regardless of the type of device that constitutes a given peer202, that peer 202 can store all or a portion of archived/aggregateddata 108 as well as post-aggregated, processed data. In other words,multiple peers 202 can each store a respective portion of data 108. Insome cases, each portion of data (labeled data 108 ₁-108 _(N)) can bemutually exclusive (e.g., no file included in data 108 exists on morethan one peer 202), while in other cases each portion can be unique(e.g., the set of files included in each portion of data 108 is uniqueeven though multiple peers 202 can include the same file), while instill other cases substantially identical file sets can be included onmultiple peers 202 or devices associated therewith. Alternatively, thedata can persist and be managed at a central storage 206, and a subsetthereof selectively streamed to respective users 106 on an as needed ordesired basis.

Furthermore, regardless of the networking topology, it should beappreciated and understood that any portion of data 108 hosted by peer202 can reside not only on the peer 202 proper, but also on devicesattached to or inserted in that peer 202. For example, consider a CD-ROMdrive (e.g., attached device) associated the user's laptop (e.g., peer202).

Regardless of whether or not data storage service 104 is implementedaccording to a distributed networking topology, data storage service 104can, according to one or more aspects, maintain a network-accessibledata repository that stores or hosts at least a portion of data 108.Thus, one example device that embodies a peer 202 can be device 206illustrated as an example for peer 202 ₁. Likewise, one or more peers202 can be embodied by a device 208, which can be, e.g., a home computeror laptop associated with user 106, as illustrated in connection withpeer 202 ₂. Moreover, other devices 210 that are not directly associatedwith user 106 or data storage service 104 can embody a peer (e.g., peer202 _(N)) as well. For example, peers 202 can be hosted by contacts ofuser 106 or members of a community associated with user 106 or datastorage service 104.

It should be appreciated that the examples depicted for each peer 202₁-202 _(N) are intended to be exemplary in nature, and need notnecessarily be representative of ordering or a constituent compositionof peers 202. Moreover, data storage service 104 need not in all aspectsmaintain any data repository at all. For example, peers 202 need notinclude data storage service 104, and data 108 regardless ofapportionment can be stored by other devices or data stores, even if atleast transactions 110 are managed by data storage service 104.

Continuing the discussion of FIG. 1, system 100 can further includemonitor component 112 that can perform a variety of examination andmonitoring tasks. For example, in accordance with one or more aspects ofthe claimed subject matter, monitor component 112 can monitor user 106action, context, state, etc., in connection with data collectionfeatures discussed above. An aggregation component 114 can process,structure, filter, and/or aggregate the data to facilitate utilizing theaggregated data in connection with provisioning of services torespective users 106. The aggregated, processed, and/or conditioned datacan be employed to populate a knowledge base or data model residing instorage 104. System 100 can also include analysis component 120 that candetermine a respective cost-benefit 122 for each of a plurality of datamonitoring, collection, aggregation, and/or provisioning scenarios.

Accordingly, system 100 facilitates a dynamic data aggregation schemethat can be employed to build a knowledge base of the mesh network.Information regarding user or device interaction with the mesh networkcan be collected, aggregated, analyzed, conditioned, filtered, mined, orthe like to improve accuracy of a data model that facilitatesprovisioning of services associated with the mesh network. As notedsupra, interaction with the mesh network can occur passively (e.g., as abackground application not generally visible to the user), or activelywhere for example the user can initiate collecting or logging ofinformation from/to the mesh network. Various incentives can be employedto facilitate gathering of such user or device data. As a result ofbuilding a robust and accurate mesh network services model, targetedservices can be provided that facilitate provisioning of services tousers or devices within the mesh network. An aspect of the claimedsubject matter relates to optimizing the mesh network and interactiontherewith so as to facilitate provisioning of services. User and/ordevice data can be collected and mined in connection with improvingservices provisioned to users/devices. Suggestions regarding products orservices based on the data aggregation and/or mappings can be improved.Automated actions can be taken based on a utility-based analysis, e.g.,a cost benefit analysis where the benefit associated with a particularautomated action with a given confidence level outweighs the cost oftaking an incorrect or undesired action

FIGS. 3-11 illustrate various exemplary methodologies associated withaggregating, analyzing, data mining, and provisioning of services inconnection with a mesh network. It is to be appreciated that the actsare described in connection with functional modules or blocks. Moreover,the order in which the acts are described is intended to benon-limiting, and any suitable arrangement of modules or blocks, orsubset thereof can be implemented in connection with carrying outaspects described and claimed herein.

Turning now to FIG. 3, a methodology in connection with collecting datafrom a user or device to facilitate populating a knowledge database ormodel of a mesh network is described. At 300 identification, inferenceor determination is made of a user or device entering into the meshnetwork. This act can be accomplished through any of a variety ofsuitable manners. For example, a user device logging onto an accesspoint within the mesh network. It is to be appreciated thatauthentication schemes can be employed to facilitate identifying theuser as well as determine level of access rights and privileges. At 310,a manner of collecting data from the user or device is determined. Forexample, the data can be collected passively, e.g., as a backgroundapplication or service, or actively (e.g., direct interaction with theuser). At 320, level and type of data collection is determined. Thevolume of data as well as type of data to be collected is determined. Itis appreciated that as device capabilities increase over time the amountand type of data that can be collected from respective devices can bevoluminous. Accordingly, selective data collection schemes can beemployed to facilitate gathering information relevant to building themesh network data model or knowledge base. For example, various types ofcontextual information or the like can be employed to facilitateselective data collection. If a user is pointing a device at a certainitem, data collection can be focused on the POI and data not deemedrelevant to the POI or user goal is not collected. At 330, datacollection is initiated.

FIG. 4 illustrates a methodology relating to aggregating collected datato facilitate building the mesh network data model or knowledge base. At400 collected data is conditioned or schematized to facilitate workingtherewith or analyzing the data. At 410, the conditioned data isprocessed or analyzed. For example, the data can be learned such thatmappings, correlations, dependencies, etc, are identified. At 420 a datamodel is generated, or for existing data models it is refined based onnewly collected data as well as aged out data. The data aggregation canfacilitate provisioning of services to respective users in a tailoredmanner. For example, based on aggregated and learned data, the datamodel can infer or determine that other individuals similar to thecurrent user (e.g., in demographics, interest group, genre, currentgoal, or the like) can provide recommendations, automated action, etc.

FIG. 5 illustrates a high-level methodology in connection withprovisioning of services within a mesh network. At 500, identification,inference, or determination is made that a user or device has enteredinto the mesh network. At 510, the user or device is analyzed. Forexample, user or device location, state, speed, direction, intent isinferred or determined. It is to be appreciated that artificialintelligence based techniques can be employed in connection with makingsuch inferences or determinations. Statistical, probabilistic, linear,non-linear, deterministic, non-deterministic, and other suitablemathematical techniques can be utilized in connection with gleaningrelevant context-based information regarding the user or device.Additionally, extrinsic evidence (e.g., time of day, weather, businessconditions, third party information, historical data, user preferences,etc.) can be considered. At 520, a mapping is performed in connectionwith mapping services to be provisioned to the user from the meshnetwork. Given a certain set of evidence (e.g., collected, stored,received . . . ) most suitable services given user/device state,desires, expectations, etc. are identified for potential provisioning tothe user/device. A utility-based analysis can be employed that factorsthe cost of provisioning an undesired service to the user versus thebenefit of provisioning a service that is desired by the user or device.At 530 a determination is made to provision or not provision varioussubsets of available services.

FIG. 6 illustrates an example provisioning scenario. At 600, user ordevice intent or goals are inferred or determined. The inference ordetermination can be effected via numerous manners such as, for example,employing state information, contextual information, historical data,preference information, extrinsic evidence, etc. As a function of theinference or determination, at 610 a subset of available services areidentified for provisioning as well as a subset of available servicesare identified for not provisioning (e.g., blocking or filtering). At620 a utility based analysis is performed in connection withprovisioning various services. The cost benefit analysis can identifyfor example which services to provision, order of provisioning,reordering of provisioning, when, where, and how to provision respectiveservices. The above-noted data model or knowledge base is employed inconnection with such utility-based analyses. Demographic information,state information, preferences, what like people have done, historicaldata, available resources, user or device context, value of information,authentication level, privacy concerns, cost of interruption, usercognitive load, temporal value of information, staleness of data,priority of information, etc. are examples of data types, metrics, orinformation that can be factored in connection with provisioning or notprovisioning of services within the mesh network.

FIG. 7 illustrates an advertising methodology in connection with aspectsof the claimed subject matter. At 700, user or device intent or goalsare determined. At 710 as a function of the inferred or determinedgoals, targeted advertisements are identified that have high probabilityof success with the targeted user or device. Accordingly, factors suchas user or device state, location, demographics, direction of movement,speed, context, preferences, and other metrics or data types describedherein can be considered in connection with provisioning of targetedadvertisements. At 720, any one or more of ordering, display, mode ofdelivery, when, where, or how to deliver the targeted advertisement(s)is determined. At 730 the subset of targeted advertisements areprovisioned. It is to be appreciated that pricing of targetedadvertisements or impressions can be a function of confidence level ofclick through rate. For example, a mesh network host service could varypricing of impressions to merchants as a function of likelihood ofsuccess of the targeted advertisement that is provisioned as a functionof the knowledge data base or data model. The richness of the data modelor knowledge base increases probability of provisioning of services oradvertisements with high success rate. Accordingly, pricing can vary asa function of the historical or expected success rate. At 740, anoptional act of feeding back results of targeted advertisementprovisioning can be performed in connection with training the data modelor refining the knowledge base. Use of feedback facilitates improvingaccuracy of the model as well as adapting it to changing trends,preferences, conditions, etc.

FIG. 8 illustrates a methodology for effecting pricing of advertisementsor services within a mesh network. At 800 user, device, or serviceprovider goals are inferred or determined. It is to be appreciated thatat any given time, a matrix of price points, user, device, customer,service provides goals or interest are in variance. The subjectmethodology at 810 performs optimization analyses in connection withdynamic data sets to set pricing points in a manner to facilitatemaximizing utility of service provisioning. For example, based on userstate, provider inventory, available resources an optimal price can bedetermined that increases likelihood of sale or a service or good. At820 a selective set of services are provisioned as a function of theanalyses. For example, given a certain set of evidence a same set ofservices may be provisioned to user 1 at a higher price point than user2. Likewise, cost for an advertising impression can also be dynamicallyvaried across potential advertisers. A static pricing model can alsooptionally be employed as well as a temporal model where pricing changesover time but not necessarily each target individual.

FIG. 9 illustrates a methodology for dynamically modifying services tobe provisioned, At 900 activities associated with a set of users/deviceswithin the mesh network are modified. For example, population densities,traffic pattern, resource utilization, service throughput, etc. At 910the activity data is analyzed in connection with modifying provisioningof services to another set of users/devices. It is to be appreciatedthat there can be commonality between various subsets of users/devicesacross the respective sets. For example, if there is a high density oftraffic at a coffee shop, and the frequency of users/devices enteringthe shop is greater than those exiting an inference can be made thatthere may be a long wait time. Moreover, based on the analyzed data anexpected wait time can be calculated within a reasonable standarddeviation of error. Based on the analyses, at 930 services to beprovisioned can be tailored or modified. For example, a user could beadvised to not patronize the coffee shop he/she regularly goes tobecause of traffic, long wait time, or the like, and to go to anothercoffee shop that overall will provide for the user to make an importantmeeting on time. Accordingly, shopping can be substantially optimized tomeet current user goals and timeliness.

FIG. 10 illustrates a methodology relating to data collection. At 1000,data related to user or device context is collected from one or moredevices. It is to be appreciated that a user often is in proximity toand/or interacting with multiple device concurrently. For example, auser may be in an automobile, using a cell phone as well as a navigationsystem, and on-board display as well as audio. The number of devices,types, when, where, and how can provide rich context and stateinformation about the user and/or device of interest. At 1010, theavailable data is filtered as a function of relevancy in connection withaggregating the data, and processing it to populate the knowledge baseor data model. At 1020, the filtered data is aggregated and populatedinto a data store.

FIG. 11 illustrates a methodology for matching a user or device with aset of services. At 1100, user activity is determined or identified. Asdiscussed above, intrinsic as well as extrinsic information can beemployed to make such determination. One goal is to identify user state,preferences, desires, etc. so as to optimize provisioning of services tothe user in connection with maximizing user satisfaction as well asoptimizing return on investment to service providers. At 1110, a set ofavailable services are identified that may be suitable for provisioningto a particular user. Demographics, social networks, preferences, userstate, device state, device capabilities, historical information,available resources, traffic, price, weather, urgency, priorities, usergoals, etc. are some factors that can be considered in connection withidentifying suitable services for provisioning. At 1120, a matchingfunction is performed to match most suitable services to provision givena set of evidence. Optionally, a utility based analysis can be performedthat effects a cost benefit analysis in connection with servicesprovisioning. At 1130, a set of services deemed most appropriate areprovisioned to the user or target device.

FIGS. 12 and 13 illustrate various methodologies in connection withemployment of pointing based services where a user can point a device ina particular direction or at an item of interest. The act of pointing adevice provides for focusing on a particular category of interest, andallows for filtering out data that is not relevant. FIG. 12 is a flowdiagram of an exemplary non-limiting process for using a device andservices as described herein. At 1200, a place where a portable deviceis located is determined based on position information. At 1210, thedevice interacts with an item of interest in the place via directionbased services. At 1220, a desired characteristic for the item ofinterest is indicated. At 1230, results regarding the item of interestare received later when the characteristic is satisfied. At 1240,updated content about the item of interest can be provided.

FIG. 13 is a flow diagram of a non-limiting scenario for the process ofFIG. 12. At 1300, a place where the portable device is located isdetermined based on position information. At 1310, the device interactswith an item of interest in the place via direction based locationservices as described elsewhere herein. At 1320, the user identifies atarget price for the item of interest. At 1330, results respecting theitem of interest are delivered later when the price drops, e.g., 2months later. At 1340, the content about the item of interest can beupdated on an ongoing basis or at the time of delivery of the delayedcontent (e.g., new or updated advertisement, recent user reviews, etc.).

It is to be appreciated that switching among channels can be effectedfor any of missing infrastructure to engage in pointing based services.users can engage pointing based services using a first network, but thenone or more aspects of connectivity are lost, connectivity can beregained from a second network, e.g., local Bluetooth network, otheruser pointing devices, etc. Users who have opted in for mesh devicecooperation can share processing resources, information missing fromother devices within the cooperative network, for instance, if onedevice has the missing information in its local cache, etc.

The possibilities for mesh networking based on movable endpoints in apointing based device system are limitless. For instance, one meshnetwork scenario would be to determine actual traffic patterns byuploading user path data from millions of users over the country for oneyear. What would emerge from such a large mesh network of cooperatingusers is data about roads that statistically represents traffic forvarious conditions on those roads, e.g., at night, when raining, time ofday, etc. Thus, a driving or direction service predicated on suchinformation and the actual paths that drivers take down the roadsincluding all of their turns can be more effective than the mathematicalassumptions made by navigation systems today.

User data, user paths, user transactions, and interactions can thus beuploaded to a network service that tracks business intelligence aboutpeople or groups of people. Business intelligence can be created fromthese types of social scenarios and user interactions. Users can optinto one or more cooperative mesh network scenarios, e.g., “use my cardata to build road data.” Data from each user can collected andaggregated over time and, the aggregate data examined for macro trendsand patterns. As a result of the key trends and patterns discovered,services can be built on key trends and patterns, such as the improveddirections based on actual user path data. The trends and patterns canbe organized into additional reports and subscription data in whichvarious marketing or other organizations may be interested.

In addition, customized scenarios can be designed for different types ofdevices, or for different types of placement of those devices. Forinstance, a set of services for a biker is different than the set ofservices that a car driver wants. Thus, that different kinds of movingobjects inherently have different requirements, e.g., a biker does notneed gas.

In this regard, leveraging digital compasses and location services toprovide direction and location information enables a next-generation ofdirection or pointer based location search services, scan services,discoverability services, etc., where the digital compass and GPS can beused to point at objects of interest, thus defining the entry point forone or more data transactions between the device and one or more thirdparty devices providing service(s) for the objects of interest at whichthe device is pointed.

As reflected in various embodiments, a device is provided that can honein on, interact with, or otherwise transact with, a specific object orspecific objects of interest by way of location and direction of thedevice, creating a new advertising model not previously known. As anexample, when a user interacts with a particular product on a shelf at aretail store in connection with a direction based service, this createsan opportunity for anyone having an interest in the particular productto engage the user, e.g., communicate some information to that user. Anycontext that can be discerned from the user's actions and interactionscan also be taken into account when acting on the opportunity. In thisregard, users can interact with the endpoints in a host of contextsensitive ways to provide or update information associated withendpoints of interest, or to receive beneficial information orinstruments (e.g., coupons, offers, etc.) from entities associated withthe endpoints of interest, and any of such actions can be joined to forma mesh network. With location services, it can be determined that auser's device is physically inside an actual store, or near a windowdisplay of a store. Coupling that to the user's interacting with anobject of interest with direction information to enable direction-basedservices results in a new opportunity to take action based on theinteraction with specific items.

In one embodiment, a portable electronic device is provided having apositional component for receiving position information as a function ofa location of the portable electronic device; and at least one processorconfigured to process the position information to determineidentifier(s) of points of interest associated with the location of theportable electronic device and based on intent information determinedfor the portable electronic device and the identifier(s), a set of delaycriterion are set for later interaction with the given points ofinterest represented by the identifier(s).

As mentioned, a device can include a directional component that outputsdirection information as a function of an orientation of the portableelectronic device and that facilitates determining an intent of thedevice. The directional component can optionally be a digital compassthat outputs the direction information. The device can determine asubset of items of interest relative to candidate items of interestwithin a 3-D space as a function of the positional information or thedirection information.

The device can request delayed content based on a selection of an itemof interest and the identifier(s). The request for the delayed contentcan be based on a scan of an encoding associated with an item ofinterest and the identifier(s). The request for delayed content can bebased on a keyword received as input by the device and theidentifier(s). The request for delayed content can be based on theintent information and the identifier(s) from at least one networkservice. The request for delayed content can also be automatic, or madeby other explicit or implicit request by the user.

At a later time, and potentially from a different device, a contentpackage can be received based on the request for the delayed contentfrom the network service. The device can optionally include a display orsound devices, such as speakers, to display or render some or all of thegraphical (e.g., text, icon, image data, video data, etc.) and/or audiocontent of the content package.

An initial interacting can include orientating the device toward someitem(s) of interest and determining direction information associatedwith the orientation of the device from which a subset of the item(s) ofinterest are identified. For instance, interacting can include pointingthe device in a direction defining a pointing line generally towardsitems of interest in the place(s) and determining a set of candidateitems of interest as a subset of items of interest that substantiallyintersect with the pointing line, and enabling the selection of one ormore items from the set of candidate items.

In one embodiment, a method for a device provisioned for direction basedservices comprises determining direction information associated with apointed to direction relative to a pre-defined orientation of the deviceand identifying POIs within an area defined as a function of the pointedto direction including determining which of a set of POIs intersect withthe area. Next, information corresponding to the POIs identified withinthe area is displayed, e.g., on a map or list, and POIs identifiedwithin the area can be designated for a delayed interaction at a latertime. In one embodiment, IDs associated with the designated POIs aretransmitted to a network service enabling information about thedesignated POIs to be exposed at the later time, e.g., from a differentform factor device.

The designation of POIs for later interaction can include explicit inputwith respect to the designated one or more POIs, such as one or more ofa gesture input, a keyword input, an audio input, a video camera inputor a touchscreen input with respect to the one or more POIs. Thedesignation of POIs for later interaction can include implicit inputwith respect to the designated one or more POIs including makinginferences about the delayed interaction at the later time based on acontext of present interaction.

The displaying of POI information can be made on a topographical mapvisually representing at least the area defined as a function of apointed to direction and graphical indications of the POIs can bedisplayed within the area at corresponding locations on thetopographical map view. The POIs can also be represented in a filteredlist view, e.g., filtered by restaurants in the area. The designating ofPOIs can include designating pre-defined criteria explicitly orimplicitly defining the delay of the delayed interaction. Thedesignating can include marking one or more POIs with touchscreen inputrelating to the one or more designated POIs, tagging the one or morePOIs with tag information defining the delayed interaction, or otherways to designate POIs for later interaction.

In another embodiment, a portable electronic device includes apositional component for receiving position information as a function ofa location of the portable electronic device and a directional componentthat outputs direction information as a function of an orientation ofthe portable electronic device. In addition, the device includes aprocessor configured to process the position information and thedirection information to determine identifiers or IDs of POIs within apre-defined geographical area of the device, interact with a selectedID, receive information about the POI corresponding to the selectedidentifier, and receive input regarding the selected ID defining afuture interaction.

Information about the selected ID defining the future interaction istransmitted along with the point of interest to a network service. Inone embodiment, a pointer structure is provided on the device thatvisually indicates the orientation of the portable electronic devicebased upon which the directional component outputs the directioninformation. For example, this could be a triangular structure thatcomes to a point to show a primary orientation of the device. This couldalso be indicated on the display of the device during provision ofdirection based services.

In one embodiment, the position information and the directioninformation determine a pointing line and a set of candidate points ofinterest are determined as a subset of points of interest thatsubstantially intersect with a function based on the pointing line. Anintersection test for determining subsets of points of interest caninclude defining an arc based on an angle with respect to a pointingline, defining a cone based on an angle with respect to the pointingline, or a line function defining a rectangular space oriented along thepointing line (2-D or 3-D depending on the application). A speaker canrender audio content if a condition upon which the future interaction ispredicated occurs. The directional component can be a digital compassthat outputs the direction information.

In another embodiment, a method comprises determining a place in which aportable device is located based on location information determined forthe device and identifying a subset of items of interest in the placeincluding determining an orientation of the device based on directioninformation of the device and determining the subset of items ofinterest in the place as a function of the orientation. Next, input withrespect to an item of the subset of items is received as well as inputdefining a delayed interaction with the item or place.

The delayed interaction can include receiving a notification when acharacteristic of the item meets a pre-defined condition, such as when aprice of the item meets a target price condition, thereby initiating thedelayed interaction. One way of identifying and designating an item fordelayed interaction can be with a scan input from scanning or imaging abar code associated with the item of interest.

FIG. 14 is a block diagram illustrating some concepts of one or moreembodiments for enabling delayed interaction with endpoints in adirection based location system. In this regard, two main things arespecified by the device participating in direction based services 1420.First, the device provides POI information 1400 from pointing with thedevice, i.e., the device identifies nearby POIs of particular interestto a user. This can be done explicitly 1402 or implicitly 1404. Also,the device associates criteria for delay 1410 with the POIs. This toocan be done explicitly 1412 or implicitly 1414. Together, the POIinformation 1400 and delay information 1410 are transmitted to directionbased services 1420, which enables a whole host of scenarios 1430 forlater interaction with the POIs 1400 according to the criteria 1410being satisfied.

FIG. 15 is an exemplary non-limiting diagram of an architecture forachieving one or more embodiments described herein. At the device layerLayer1 for specifying delayed POI information, location information1500, direction information 1502 and user intent information 1504 can beinput to a Layer2 with various services 1510, including web services1512, cloud services 1514, other data services 1516, etc. Any ofservices 1510 can have input to a set of brick and mortar storedatabases in Layer3, such as data store(s) 1520, 1522, 1524, etc. or setof online or electronic retailer databases in Layer4, such as datastore(s) 1530, 1532, 1534, etc. In this regard, user intent 1504 coupledwith a place of the device can be utilized by one or more services 1510to retrieve and deliver custom content 1540 to the device based on theintent and place of the device, but at a later time according to a setof explicit or implicit criteria.

FIG. 16 is a flow diagram of a scenario where a user delays interactionwith a point of interest. At 1600, a user points a pointer device in oneor more directions to define scope of endpoints. At 1610, the userreceives an indication of one or more endpoints within scope in responsefrom a network service. At 1620, the user marks endpoint(s) for laterinteraction or viewing. At 1630, when the user reconnects to theservice, e.g., from a PC, the user can receive reminders about markedendpoints. Other ways for triggering the interaction can be employed at1630 as described elsewhere herein. The user can follow through withinteraction/viewing at 1640, as desired.

FIG. 17 is a flow diagram illustrating an exemplary process fordesignating POIs for delayed interaction in connection with directionbased services. At 1700, direction information is determined from apointed to direction relative to a pre-defined orientation. At 1710,POIs are identified within an area defined as a function of the pointedto direction and it is determined which POIs intersect the area and arewithin scope of a given user experience. At 1720, informationcorresponding to the POIs identified within the area is displayed, e.g.,on a map or in a list. At 1730, the POI(s) identified within the areaare designated for a delayed interaction at a later time. At 1740, theinformation (e.g., ID information) associated with the POIs designatedfor later interaction is transmitted to a network service enabling laterinteractions.

FIG. 18 illustrates an exemplary non-limiting device 1800 includingprocessor(s) 1810 having a position engine or subsystem 1820 fordetermining a location of the device 1800 and a direction engine orsubsystem 1830 for determining a direction or orientation of the device1800. Then, by interacting with local application(s) 1840 and/orservice(s) 1870, content can be delivered to the device, which istailored to device intent and a place in which the device is present.The tailored content can be rendered by graphic subsystem or display/UI1850 or audio subsystem 1860. In one non-limiting embodiment, pointstructure 1890 is included, e.g., a triangular piece that points alongan orientation line 1895 upon which directional calculations are based.Similarly, the orientation line 1895 can be indicated by graphicssubsystem display/UI 1850 with or without point structure 1890. In thisregard, various embodiments herein enable delayed POI ID information1880 to and from services 1870 so that the delayed interactions canoccur in the future as assisted by services 1870.

FIG. 19 is a flow diagram illustrating a process for delayinginteraction with respect to a specific item within an identified place.At 1900, a place at which a portable device is located is determinedbased on location information of the device. At 1910, an orientation ofthe device is determined based on direction information of the deviceand a subset of items of interest are identified in the place as afunction of the orientation. At 1920, an item of the subset of items canbe selected and a delayed interaction with the item (or place) isthereby enabled by direction based services.

FIG. 20 illustrates a mobile computing device 100 according to anembodiment. In this regard, a set of services 2060 that support delayedinteraction with points of interest can be built based on locationinformation 2022 and direction information 2032 collected by a mobiledevice, such as a phone. For instance, location information 2022 can berecorded by a location subsystem 2020 such as a GPS subsystemcommunicating with GPS satellites 2040. Direction or pointinginformation 2032 can be collected by a direction subsystem 2030, such asa compass, e.g., gyroscopic, magnetic, digital compass, etc. Inaddition, optionally, movement information 2012 can be gathered by thedevice 2000, e.g., via tower triangulation algorithms, and/oracceleration of the device 2000 can be measured as well, e.g., with anaccelerometer. The collective information 2050 can be used to gain asense of not only where the device 2000 is located in relation to otherpotential points of interest tracked or known by the overall set ofservices 2060, but also what direction the user is pointing the device2000, so that the services 2060 can appreciate at whom or what the useris pointing the device 2000.

In addition, a gesture subsystem 2070 can optionally be included, whichcan be predicated on any one or more of the motion information 2012,location information 2022 or direction information 2032. In this regard,not only can direction information 2032 and location information 2022 beused to define a set of unique gestures, but also motion information2012 (such as speed and acceleration) can be used to define a moresophisticated set of gestures.

FIG. 20 thus illustrates a gesture subsystem 2070 can optionally beincluded in a device 2000. In this regard, one can appreciate that avariety of algorithms could be adopted for a gesture subsystem 2070. Forinstance, a simple click-event when in the “pointing mode” for thedevice 2000 can result in determining a set of points of interest forthe user. Another gesture on top of that pointing gesture with respectto a POI can result in delaying interaction with that POI.

In this regard, a device can include a variety of spatial and mapcomponents and intelligence engines to determine intersections fordirectional arcs (or cones in 3-D). For instance, objects of interestcould be represented with exact boundaries, approximated with spheres,subshells (stores in a mall) of a greater shell (mall), hierarchicallyarranged, etc. Dynamically generated bounding boxes can also beimplemented work, i.e., any technique can be used to obtain boundaryinformation for use in an intersection algorithm. Thus, such boundariescan be implicitly or explicitly defined for the POIs.

Thus, a device can include an intersection component that interpretspointing information relative to a set of potential points of interest.The engine can perform such intersections knowing what the resolution ofthe measuring instruments are on the device, such as a given resolutionof a GPS system. Such techniques can include taking into account how fara user is from a plane of objects of interest, such as items on a shelfor wall, the size of the item of interest and how that is defined, aswell as the resolution of location instrumentation, such as the GPSsystem. The device can also optionally include an altimeter, or anyother device that gives altitude information, such as measuring radar orsonar bounce from the floor. The altitude information can supplementexisting location information for certain specialized services wherepoints of interest vary significantly at different altitudes. It isnoted that GPS itself has some information about altitude in itsencoding.

FIG. 21 is a block diagram illustrating an exemplary non-limitingexchange between a device 2100 and service 2110. After start 2102, anexample request for illustrative purpose is made by a device 2100 to aservice 2110, which includes data related to the location of the device,a given POI, and information about delaying the interaction. Forinstance, then, at 2115, the service 2110 gets all offers for the POI2115 and/or at 2120, gets the offers for the given location. At 2125, orearlier, it is determined if the delay criteria have been met for thegiven POI, if so, the service 2110 may get updated content associatedwith the location 2130 along with an optional branded user interface at2135. At 2140, assuming the delay criteria have been met, an updatedcontent package is created and delivered to the device 2100 at 2145. Thedevice can undergo a check for the device at 2150. The delayed or futureinteraction can take place at 2155. Optionally, based on an advertisingmodel, the content providers or owners can be billed at 2160.

FIG. 22 illustrates a general block diagram for an optional encodingtechnique for POI information. In this regard, various pieces of staticand dynamic information 2202, 2204, 2206, 2208, 2210, etc. for a POI,which are normally represented in UI 2200 of the device, can also beencoded as an image or a bar code 2220, or some other device readablecompact encoding. Then, a user can scan an item of interest, and coupledwith presence in a physical store, a request 2215 can be made to aservice 2240 with a key representing the scanned item and informationrepresenting the place, whereby the service 2240 determines content 2225to return to the device 2200 based on the scanned item and the place. Inaddition, delay criterion 2225 specify how to delay the interaction withthe scanned item.

For instance, in an optional Quick Response (QR) support embodiment,decompression allows users to take pictures of a QR code and process itscontents where information has been encoded into a sticker/printout fordisplay outside of a business (e.g., in the form of a copyrighted URL).The code need not be a QR code, but could be any code that can be reador scanned or processed to determine its underlying content. Forinstance, with a visual representation, a picture can be taken andprocessed, or with the bar code, the device can scan it. RFidentification technology could also be used. For the avoidance ofdoubt, any encoded image format can be used, like a bar code, only oneexample of which is a QR code.

In effect, this enables a query for POI information via a QR code orother encoding. The user scans or images the code with a device 2230,and then transmits the code to the service, which translates the codeinto static and dynamically updated user information for display as a UI2200 (or other user interface representation) so that the user can queryabout a POI merely by pointing at it. A URL for the POI can also beencoded in a format such as a QR code. In one non-limiting embodiment,the user can point the device at a QR code, and decode a given imagewith the QR code.

FIG. 23 illustrates at a high level, via a block diagram, a beneficialadvertising model enabled by a direction/location based services withdelayed interaction with endpoints as described in one or moreembodiments herein. For instance, scanned items 2300 for delay, orpointed to items 2300 for delay, or any other action taken with respectto items 2300 for delay can be sent as information 2305 to a service2310 that brokers interested third parties 2320 or 2330 who wish toadvertise given the place and particular items 2300. Accordingly, suchthird parties 2320 or 2330 (third parties may be misleading becausethird parties can include parties related to a retail establishmentwhere the device is currently located) can provide content as part ofinteractions 2325 or 2335 as part of a push or pull experience from theuser perspective. This opportunity to provide content in a delayedmanner enables services 2310 to notify 2315 parties 2320 interested inthe delayed interaction. This beneficial information provided to thirdparties 2320 or 2330 about potential delayed interactions withparticular POIs and places is therefore an opportunity to monetize thetransaction back to those who benefit from a resulting transaction oradvertising opportunity.

FIG. 24 is a block diagram illustrating a vast wealth of actions andinteractions that can help define intent/context 2420 to delay for agiven POI and location at which the device is present. For instance,text 2400 may be received by the device, a product search query 2402local to the store, bar code scan 2404, image scan 2406, explicitdesignation of a product (e.g., by pointing at a product, or taking animage of the product and performing image recognition) 2408, pricecompare request 2410, gesture input 2412, other interaction 2414, etc.can all be taken into account in discerning intent of the device at agiven place, along with direction information 2450. This combined withlocation information 2440 for discerning the place in which the deviceis in results in advertising opportunities 2430 for a whole host ofthird party advertising transactions for delayed delivery to the device.

Supplemental Context Regarding Pointing Devices, Architectures andServices

The following description contains supplemental context regardingpotential non-limiting pointing devices, architectures and associatedservices to further aid in understanding one or more of the aboveembodiments. Any one or more of any additional features described inthis section can be accommodated in any one or more of the embodimentsdescribed above with respect to delayed direction based services at aparticular location for given POI(s). While such combinations ofembodiments or features are possible, for the avoidance of doubt, noembodiments set forth in the subject disclosure should be consideredlimiting on any other embodiments described herein.

As mentioned, a broad range of scenarios can be enabled by a device thatcan take location and direction information about the device and build aservice on top of that information. For example, by using anaccelerometer in coordination with an on board digital compass, anapplication running on a mobile device updates what each endpoint is“looking at” or pointed towards, attempting hit detection on potentialpoints of interest to either produce real-time information for thedevice or to allow the user to select a range, or using the GPS, alocation on a map, and set information such as “Starbucks—10% offcappuccinos today” or “The Alamo—site of . . . ” for others to discover.One or more accelerometers can also be used to perform the function ofdetermining direction information for each endpoint as well. Asdescribed herein, these techniques can become more granular toparticular items within a Starbucks, such as “blueberry cheesecake” ondisplay in the counter, enabling a new type of sale opportunity.

Accordingly, a general device for accomplishing this includes aprocessing engine to resolve a line of sight vector sent from a mobileendpoint and a system to aggregate that data as a platform, enabling ahost of new scenarios predicated on the pointing information known forthe device. The act of pointing with a device, such as the user's mobilephone, thus becomes a powerful vehicle for users to discover andinteract with points of interest around the individual in a way that istailored for the individual. Synchronization of data can also beperformed to facilitate roaming and sharing of POV data and contactsamong different users of the same service.

In a variety of embodiments described herein, 2-dimensional (2D),3-dimensional (3D) or N-dimensional directional-based search, discovery,and interactivity services are enabled for endpoints in the system ofpotential interest to the user.

The pointing information and corresponding algorithms depend upon theassets available in a device for producing the pointing or directionalinformation. The pointing information, however produced according to anunderlying set of measurement components, and interpreted by aprocessing engine, can be one or more vectors. A vector or set ofvectors can have a “width” or “arc” associated with the vector for anymargin of error associated with the pointing of the device. A panningangle can be defined by a user with at least two pointing actions toencompass a set of points of interest, e.g., those that span a certainangle defined by a panning gesture by the user.

In one non-limiting embodiment, a portable electronic device includes apositional component for receiving positional information as a functionof a location of the portable electronic device, a directional componentthat outputs direction information as a function of an orientation ofthe portable electronic device and a location based engine thatprocesses the positional information and the direction information todetermine a subset of points of interest relative to the portableelectronic device as a function of at least the positional informationand the direction information.

The positional component can be a positional GPS component for receivingGPS data as the positional information. The directional component can bea magnetic compass and/or a gyroscopic compass that outputs thedirection information. The device can include acceleration component(s),such as accelerometer(s), that outputs acceleration informationassociated with movement of the portable electronic device. The use of aseparate sensor can also be used to further compensate for tilt andaltitude adjustment calculations.

In one embodiment, the device includes a cache memory for dynamicallystoring a subset of endpoints of interest that are relevant to theportable electronic device and at least one interface to a networkservice for transmitting the positional information and the directioninformation to the network service. In return, based on real-timechanges to the positional information and direction/pointinginformation, the device dynamically receives in the cache memory anupdated subset of endpoints that are potentially relevant to theportable electronic device.

For instance, the subset of endpoints can be updated as a function ofendpoints of interest within a pre-defined distance substantially alonga vector defined by the orientation of the portable electronic device.Alternatively or in addition, the subset of endpoints can be updated asa function of endpoints of interest relevant to a current context of theportable electronic device. In this regard, the device can include a setof Representational State Transfer (REST)-based application programminginterfaces (APIs), or other stateless set of APIs, so that the devicecan communicate with the service over different networks, e.g., Wi-Fi, aGPRS network, etc. or communicate with other users of the service, e.g.,Bluetooth. For the avoidance of doubt, the embodiments are in no waylimited to a REST based implementation, but rather any other state orstateful protocol could be used to obtain information from the serviceto the devices.

The directional component outputs direction information includingcompass information based on calibrated and compensatedheading/directionality information. The directional component can alsoinclude direction information indicating upward or downward tiltinformation associated with a current upward or downward tilt of theportable electronic device, so that the services can detect when a useris pointing upwards or downwards with the device in addition to acertain direction. The height of the vectors itself can also be takeninto account to distinguish between an event of pointing with a devicefrom the top of a building (likely pointing to other buildings, bridges,landmarks, etc.) and the same event from the bottom of the building(likely pointing to a shop at ground level), or towards a ceiling orfloor to differentiate among shelves in a supermarket. A 3-axis magneticfield sensor can also be used to implement a compass to obtain tiltreadings.

Secondary sensors, such as altimeters or pressure readers, can also beincluded in a mobile device and used to detect a height of the device,e.g., what floor a device is on in a parking lot or floor of adepartment store (changing the associated map/floorplan data). Where adevice includes a compass with a planar view of the world (e.g., 2-axiscompass), the inclusion of one or more accelerometers in the device canbe used to supplement the motion vector measured for a device as avirtual third component of the motion vector, e.g., to providemeasurements regarding a third degree of freedom. This option may bedeployed where the provision of a 3-axis compass is too expensive, orotherwise unavailable.

In this respect, a gesturing component can also be included in thedevice to determine a current gesture of a user of the portableelectronic device from a set of pre-defined gestures. For example,gestures can include zoom in, zoom out, panning to define an arc, all tohelp filter over potential subsets of points of interest for the user.

For instance, web services can effectively resolve vector coordinatessent from mobile endpoints into <x,y,z> or other coordinates usinglocation data, such as GPS data, as well as configurable, synchronizedPOV information similar to that found in a GPS system in an automobile.In this regard, any of the embodiments can be applied similarly in anymotor vehicle device. One non-limiting use is also facilitation ofendpoint discovery for synchronization of data of interest to or fromthe user from or to the endpoint.

Among other algorithms for interpreting position/motion/directioninformation, as shown in FIG. 25, a device 2500 employing the directionbased location based services 2502 as described herein in a variety ofembodiments herein include a way to discern between near objects, suchas POI 2514 and far objects, such as POI 2516. Depending on the contextof usage, the time, the user's past, the device state, the speed of thedevice, the nature of the POIs, etc., the service can determine ageneral distance associated with a motion vector. Thus, a motion vector2506 will implicate POI 2514, but not POI 2516, and the opposite wouldbe true for motion vector 2508.

In addition, a device 2500 includes an algorithm for discerning itemssubstantially along a direction at which the device is pointing, andthose not substantially along a direction at which the device ispointing. In this respect, while motion vector 2504 might implicate POI2512, without a specific panning gesture that encompassed moredirections/vectors, POIs 2514 and 2516 would likely not be within thescope of points of interest defined by motion vector 2504. The distanceor reach of a vector can also be tuned by a user, e.g., via a slidercontrol or other control, to quickly expand or contract the scope ofendpoints encompassed by a given “pointing” interaction with the device.

In one non-limiting embodiment, the determination of at what or whom theuser is pointing is performed by calculating an absolute “Look” vector,within a suitable margin of error, by a reading from an accelerometer'stilt and a reading from the magnetic compass. Then, an intersection ofendpoints determines an initial scope, which can be further refineddepending on the particular service employed, i.e., any additionalfilter. For instance, for an apartment search service, endpoints fallingwithin the look vector that are not apartments ready for lease, can bepre-filtered.

In addition to the look vector determination, the engine can alsocompensate for, or begin the look vector, where the user is by establishpositioning (˜15 feet) through an A-GPS stack (or other location basedor GPS subsystem including those with assistance strategies) and alsocompensate for any significant movement/acceleration of the device,where such information is available.

As mentioned, in another aspect, a device can include a client sidecache of potentially relevant points of interest, which, based on theuser's movement history can be dynamically updated. The context, such asgeography, speed, etc. of the user can be factored in when updating. Forinstance, if a user's velocity is 2 miles an hour, the user may bewalking and interested in updates at a city block by city block level,or at a lower level granularity if they are walking in the countryside.Similarly, if a user is moving on a highway at 60 miles per hour, theblock-by-block updates of information are no longer desirable, butrather a granularity can be provided and predictively cached on thedevice that makes sense for the speed of the vehicle.

In an automobile context, the location becomes the road on which theautomobile is travelling, and the particular items are the places andthings that are passed on the roadside much like products in aparticular retail store on a shelf or in a display. The pointing basedservices thus creates a virtual “billboard” opportunity for items ofinterest generally along a user's automobile path. Proximity to locationcan lead to an impulse buy, e.g., a user might stop by a museum they arepassing and pointing at with their device, if offered a discount onadmission.

In various alternative embodiments, gyroscopic or magnetic compasses canprovide directional information. A REST based architecture enables datacommunications to occur over different networks, such as Wi-Fi and GPRSarchitectures. REST based APIs can be used, though any statelessmessaging can be used that does not require a long keep alive forcommunicated data/messages. This way, since networks can go down withGPRS antennae, seamless switching can occur to Wi-Fi or Bluetoothnetworks to continue according to the pointing based services enabled bythe embodiments described herein.

A device as provided herein according to one or more embodiments caninclude a file system to interact with a local cache, store updates forsynchronization to the service, exchange information by Bluetooth withother users of the service, etc. Accordingly, operating from a localcache, at least the data in the local cache is still relevant at a timeof disconnection, and thus, the user can still interact with the data.Finally, the device can synchronize according to any updates made at atime of re-connection to a network, or to another device that has moreup to date GPS data, POI data, etc. In this regard, a switchingarchitecture can be adopted for the device to perform a quick transitionfrom connectivity from one networked system (e.g., cell phone towers) toanother computer network (e.g., Wi-Fi) to a local network (e.g., meshnetwork of Bluetooth connected devices).

With respect to user input, a set of soft keys, touch keys, etc. can beprovided to facilitate in the directional-based pointing servicesprovided herein. A device can include a windowing stack in order tooverlay different windows, or provide different windows of informationregarding a point of interest (e.g., hours and phone number windowversus interactive customer feedback window). Audio can be rendered orhandled as input by the device. For instance, voice input can be handledby the service to explicitly point without the need for a physicalmovement of the device. For instance, a user could say into a device“what is this product right in front of me? No, not that one, the oneabove it” and have the device transmit current direction/movementinformation to a service, which in turn intelligently, or iteratively,determines what particular item of interest the user is pointing at, andreturns a host of relevant information about the item.

One non-limiting way for determining a set of points of interest isillustrated in FIG. 26. In FIG. 26, a device 2600 is pointed (e.g.,point and click) in a direction D1, which according to the device orservice parameters, implicitly defines an area within arc 2610 anddistance 2620 that encompasses POI 2630, but does not encompass POI2632. Such an algorithm will also need to determine any edge case POIs,i.e., whether POIs such as POI 2634 are within the scope of pointing indirection D1, where the POI only partially falls within the area definedby arc 2610 and distance 2620.

Other gestures that can be of interest in for a gesturing subsysteminclude recognizing a user's gesture for zoom in or zoom out. Zoomin/zoom out can be done in terms of distance like FIG. 27. In FIG. 27, adevice 2700 pointed in direction D1 may include zoomed in view whichincludes points of interest within distance 2720 and arc 2710, or amedium zoomed view representing points of interest between distance 2720and 2722, or a zoomed out view representing points of interest beyonddistance 2722. These zoom zones correspond to POIs 2730, 2732 and 2734,respectively. More or less zones can be considered depending upon avariety of factors, the service, user preference, etc.

For another non-limiting example, with location information anddirection information, a user can input a first direction via a click,and then a second direction after moving the device via a second click,which in effect defines an arc 2810 for objects of interest in thesystem as illustrated in FIG. 28. For instance, via first pointing actby the user at time t1 in direction D1 and a second pointing act at timet2 by the user in direction D2, an arc 2810 is implicitly defined. Thearea of interest implicitly includes a search of points of object withina distance 2820, which can be zoomed in and out, or selected by theservice based on a known granularity of interest, selected by the user,etc. This can be accomplished with a variety of forms of input to definethe two directions. For instance, the first direction can be definedupon a click-and-hold button event, or other engage-and-hold userinterface element, and the second direction can be defined upon releaseof the button. Similarly, two consecutive clicks corresponding to thetwo different directions D1 and D2 can also be implemented.

Also, instead of focusing on real distance, zooming in or out could alsorepresent a change in terms of granularity, or size, or hierarchy ofobjects. For example, a first pointing gesture with the device mayresult in a shopping mall appearing, but with another gesture, a usercould carry out a recognizable gesture to gain or lose a level ofhierarchical granularity with the points of interest on display. Forinstance, after such gesture, the points of interest could be zoomed into the level of the stores at the shopping mall and what they arecurrently offering.

In addition, a variety of even richer behaviors and gestures can berecognized when acceleration of the device in various axes can bediscerned. Panning, arm extension/retraction, swirling of the device,backhand tennis swings, breaststroke arm action, golf swing motionscould all signify something unique in terms of the behavior of thepointing device, and this is to just name a few motions that could beimplemented in practice. Thus, any of the embodiments herein can definea set of gestures that serve to help the user interact with a set ofservices built on the pointing platform, to help users easily gaininformation about points of information in their environment.

Furthermore, with relatively accurate upward and downward tilt of thedevice, in addition to directional information such as calibrated andcompensated heading/directional information, other services can beenabled. Typically, if a device is ground level, the user is outside,and the device is “pointed” up towards the top of buildings, thegranularity of information about points of interest sought by the user(building level) is different than if the user was pointing at the firstfloor shops of the building (shops level), even where the same compassdirection is implicated. Similarly, where a user is at the top of alandmark such as the Empire State building, a downward tilt at thestreet level (street level granularity) would implicate informationabout different points of interest that if the user of the devicepointed with relatively no tilt at the Statue of Liberty(landmark/building level of granularity).

Also, when a device is moving in a car, it may appear that direction ischanging as the user maintains a pointing action on a single location,but the user is still pointing at the same thing due to displacement.Thus, thus time varying location can be factored into the mathematicsand engine of resolving at what the user is pointing with the device tocompensate for the user experience based upon which all items arerelative.

Accordingly, armed with the device's position, one or more web or cloudservices can analyze the vector information to determine at what or whomthe user is looking/pointing. The service can then provide additionalinformation such as ads, specials, updates, menus, happy hour choices,etc., depending on the endpoint selected, the context of the service,the location (urban or rural), the time (night or day), etc. As aresult, instead of a blank contextless Internet search, a form ofreal-time visual search for users in real 3-D environments is provided.

In one non-limiting embodiment, the direction based pointing servicesare implemented in connection with a pair of glasses, headband, etc.having a corresponding display means that acts in concert with theuser's looking to highlight or overlay features of interest around theuser.

As shown in FIG. 29, once a set of objects is determined from thepointing information according to a variety of contexts of a variety ofservices, a mobile device 2900 can display the objects viarepresentation 2902 according to a variety of user experiences tailoredto the service at issue. For instance, a virtual camera experience canbe provided, where POI graphics or information can be positionedrelative to one another to simulate an imaging experience. A variety ofother user interface experiences can be provided based on the pointingdirection as well.

For instance, a set of different choices are shown in FIG. 30. UI 3000and 3002 illustrate navigation of hierarchical POI information. Forinstance, level1 categories may include category1, category2, category3,category4 and category5, but if a user selects around the categorieswith a thumb-wheel, up-down control, or the like, and chooses one suchas category2. Then, subcategory1, subcategory2, subcategory3 andsubcategory4 are displayed as subcategories of category2. Then, if theuser selects, for instance, subcategory4, perhaps few enough POIs, suchas buildings 3000 and 3010 are found in the subcategory in order todisplay on a 2D map UI 3004 along the pointing direction, oralternatively as a 3D virtual map view 3006 along the pointingdirection.

Once a single POI is implicated or selected, then a full screen view forthe single POI can be displayed, such as the exemplary UI 3100. UI 3100can have one or more of any of the following representative areas. UI3100 can include a static POI image 3102 such as a trademark of a store,or a picture of a person. UI 3100 can also include other media, and astatic POI information portion 3104 for information that tends not tochange such as restaurant hours, menu, contact information, etc. Inaddition, UI 3100 can include an information section for dynamicinformation to be pushed to the user for the POI, e.g., coupons,advertisements, offers, sales, etc. In addition, a dynamic interactiveinformation are 3108 can be included where the user can fill out asurvey, provide feedback to the POI owner, request the POI to contactthe user, make a reservation, buy tickets, etc. UI 3100 also can includea representation of the direction information output by the compass forreference purposes. Further, UI 3100 can include other third partystatic or dynamic content in area 3112.

When things change from the perspective of either the service or theclient, a synchronization process can bring either the client orservice, respectively, up to date. In this way, an ecosystem is enabledwhere a user can point at an object or point of interest, gaininformation about it that is likely to be relevant to the user, interactwith the information concerning the point of interest, and add value toservices ecosystem where the user interacts. The system thusadvantageously supports both static and dynamic content.

Other user interfaces can be considered such as left-right, or up-downarrangements for navigating categories or a special set of soft-keys canbe adaptively provided.

Where a device includes a camera, in one embodiment shown in FIG. 32, arepresentative non-limiting overlay UI 3200 is shown having 3 POIs POI1,POI2 and POI3. The POIs are overlaid over actual image data being realtime viewed on the device via an LCD screen or like display. The actualimage data can be of products on a shelf or other display or exhibit ina store. Thus, as the user aims the camera around his or herenvironment, the lens becomes the pointer, and the POI information canbe overlaid intelligently for discovery of endpoints of interest.Moreover, a similar embodiment can be imagined even without a camera,such as a UI in which 3-D objects are virtually represented based onreal geometries known for the objects relative to the user.

Thus, the device UI can be implemented consistent with a camera, or avirtual camera, view for intuitive use of such devices. The pointermechanism of the device could also switch based on whether the user wascurrently in live view mode for the camera or not. Moreover, assumingsufficient processing power and storage, real time image processingcould discern an object of interest and based on image signatures,overlay POI information over such image in a similar manner to the aboveembodiments. In this regard, with the device provided herein, a varietyof gestures can be employed to zoom in zoom out, perform tilt detectionfor looking down or up, or panning across a field of view to obtain arange of POIs associated with the panning scope.

With respect to a representative set of user settings, a number ormaximum number of desired endpoints delivered as results can beconfigured. How to filter can also be configured, e.g., 5 most likely, 5closest, 5 closest to 100 feet away, 5 within category or sub-category,alphabetical order, etc. In each case, based on a pointing direction,implicitly a cone or other cross section across physical space isdefined as a scope of possible points of interest. In this regard, thewidth or deepness of this cone or cross section can be configurable bythe user to control the accuracy of the pointing, e.g., narrow or wideradius of points and how far out to search.

To support processing of vector information and aggregating POIdatabases from third parties, a variety of storage techniques, such asrelational storage techniques can be used. For instance, Virtual Earthdata can be used for mapping and aggregation of POI data can occur fromthird parties such as Tele Atlas, NavTeq, etc. In this regard,businesses not in the POI database will want to be discovered and thus,the service provides a similar, but far superior from a spatialrelevance standpoint, Yellow Pages experiences where businesses willdesire to have their additional information, such as menus, pricesheets, coupons, pictures, virtual tours, etc. accessible via thesystem.

In addition, a synchronization platform or framework can keep theroaming caches in sync, thereby capturing what users are looking at andefficiently processing changes. Or, where a user goes offline, localchanges can be recorded, and when the user goes back online, such localchanges can be synchronized to the network or service store. Also, sincethe users are in effect pulling information they care about in the hereand in the now through the act of pointing with the device, the systemgenerates high cost per thousand impression (CPM) rates as compared toother forms of demographic targeting. Moreover, the system drivesimpulse buys, since the user may not be physically present in a store,but the user may be near the object, and by being nearby and pointing atthe store, information about a sale concerning the object can be sent tothe user.

As mentioned, different location subsystems, such as towertriangulation, GPS, A-GPS, E-GPS, etc. have different tolerances. Forinstance, with GPS, tolerances can be achieved to about 10 meters. WithA-GPS, tolerances can be tightened to about 12 feet. In turn, withE-GPS, tolerance may be a different error margin still. Compensating forthe different tolerances is part of the interpretation engine fordetermining intersection of a pointing vector and a set of points ofinterest. In addition, as shown in FIGS. 4-6, a distance to project outthe pointing vector can be explicit, configurable, contextual, etc.

In this regard, the various embodiments described herein can employ anyalgorithm for distinguishing among boundaries of the endpoints, such asboundary boxes, or rectangles, triangles, circles, etc. As a defaultradius, e.g., 150 feet could be selected, and such value can beconfigured or be context sensitive to the service provided. On-line realestate sites can be leveraged for existing POI information. Sincedifferent POI databases may track different information at differentgranularities, a way of normalizing the POI data according to oneconvention or standard can also be implemented so that the residentialreal estate location data of Zillow can be integrated with GPSinformation from Starbucks of all the Starbucks by country.

In addition, similar techniques can be implemented in a moving vehicleclient that includes GPS, compass, accelerometer, etc. By filteringbased on scenarios (e.g., I need gas), different subsets of points ofinterest (e.g., gas stations) can be determined for the user based notonly on distance, but actual time it may take to get to the point ofinterest. In this regard, while a gas station may be 100 yards to theright off the highway, the car may have already passed the correspondingexit, and thus more useful information to provide is what gas stationwill take the least amount of time to drive from a current locationbased on direction/location so as to provide predictive points ofinterest that are up ahead on the road, and not already aged points ofinterest that would require turning around from one's destination inorder to get to them.

For existing motor vehicle navigation devices, or other conventionalportable GPS navigation devices, where a device does not nativelyinclude directional means such as a compass, the device can have anextension slot that accommodates direction information from an externaldirectional device, such as a compass. Similarly, for laptops or otherportable electronic devices, such devices can be outfitted with a cardor board with a slot for a compass. While any of the services describedherein can make web service calls as part of the pointing and retrievalof endpoint process, as mentioned, one advantageous feature of a user'slocality in real space is that it is inherently more limited than ageneral Internet search for information. As a result, a limited amountof data can be predictively maintained on a user's device in cachememory and properly aged out as data becomes stale.

While there are a variety of implementations, and ways to sub-divideregions, whether overlapping or not, predictive caching and aging 3300is conceptually illustrated by FIG. 33 in which a user's presentlocation 3302 is discerned. At this point, the local cache stillincludes age out candidate location 3310, but as the velocity of theuser indicates the user will be at predicted locations 3304 and 3306 inthe future, these regions of POIs are downloaded to the mobile device.Accordingly, as the user travels to predicted location 3306, it startsto be clear that the user no longer needs the data from the age outcandidate location 3310, which can then be removed, or flagged forremoval when storage is challenged.

Accordingly, using the regional data cache, callbacks and an updatemechanism that is updated dynamically based on movement, new point ofinterest can be added by a service or by a user. Update is thusperformed continuously or substantially continuously based on updatedtravel, velocity, speed, etc. In this regard, a user can add a new pointof interest in the region, add info to a local cache, and then upload tothe zone. To appreciate the problem, the number of worldwide POIs ispractically limitless, however only a small number of POIs will berelevant to a user at a given time. Thus, predictively, a cube of datacan be taken to the device, the user can go offline such that when theuser reconnects, the device is intelligent to figure out what haschanged, been weighted, etc., so that the device can synchronize withthe network services and expose the user's changes for other people.

The predictive algorithms again depend on what the user is interested infinding, what service the user may be using, the context of the user,etc. They can also be based on velocity, direction, time, etc. Forinstance, if it is nighttime, assumptions based on demographics orpreferences may lead the device to return information about nightclubsor all night diners. Or, instead of giving directions as drivingdirections that calculate distances as absolute distances, i.e., as thecrow flies, a device can take road curves into account sinceinstantaneous pointing information on roads can be collected and handledby a corresponding service when giving driving directions. Or, asanother alternative, the direction one is heading on a road, such as ahighway with a concrete divider, is relevant to the directions that anavigation system should give. Where a U-turn is unavailable and userpasses an exit with a point of interest, for instance, directions shouldtake this into account and consider the heading of the vehicle.

Any device can include the embodiments described herein, including MP3players, such as a Zune device, GPS navigation devices, bike computers,sunglass/visor systems, motor vehicles, mobile phones, laptops, PDA,etc.

One way to obtain the service applications, assuming the underlyingmeasuring instruments to participate in the real-time gathering ofdirectional information, is to message to a service to obtain theapplication, e.g., by text messaging to service, or getting a clientdownload link. Another vehicle for enabling the service is to provide itnatively in the operating system or applications of a mobile devices.Since a hardware abstraction layer accommodates different methods forcollecting position, direction, acceleration information, the sameplatform can be used on any device regardless of the precise underlyinghardware.

In another aspect of any of the embodiments described herein, becausestateless messaging is employed, if communications drop with onenetwork, the device can begin further communicating via another network.For instance, a device has two channels, and a user gets on a bus, butno longer have GPRS or GPS activity. Nonetheless the user is able to getthe information the device needs from some other channel. Just because atower, or satellites are down, does not mean that the device cannotconnect through an alternative channel, e.g., the bus's GPS locationinformation via Bluetooth.

With respect to exemplary mobile client architectures, a representativedevice can include, as described variously herein, client Side Storagefor housing and providing fast access to cached POI data in the currentregion including associated dynamically updated or static information,such as annotations, coupons from businesses, etc. This includes usagedata tracking and storage. In addition, regional data can be a cachedsubset of the larger service data, always updated based on the region inwhich the client is roaming. For instance, POI data could include as anon-limiting example, the following information:

  POI coordinates and data //{−70.26322, 43.65412, “STARBUCK'S”}  Localized annotations //Menu, prices, hours of operation, etc  Coupons and ads //Classes of coupons (new user, returning, etc)

Support for different kinds of information (e.g., blob v structuredinformation (blob for storage and media; structured for tags,annotations, etc.)

A device can also include usage data and preferences to hold settings aswell as usage data such as coupons “activated,” waypoints, businessesencountered per day, other users encountered, etc. to be analyzed by thecloud services for business intelligence analysis and reporting.

A device can also include a continuous update mechanism, which is aservice that maintains the client's cached copy of a current regionupdated with the latest. Among other ways, this can be achieved with aping-to-pull model that pre-fetches and swaps out the client's cachedregion using travel direction and speed to facilitate roaming amongdifferent regions. This is effectively a paging mechanism for upcomingPOIs. This also includes sending a new or modified POI for the region(with annotations+coupons), sending a new or modified annotation for thePOIs (with coupons), or sending a new or modified coupon for the POI.

A device can also include a Hardware Abstraction Layer (HAL) havingcomponents responsible for abstracting the way the client communicateswith the measuring instruments, e.g., the GPS driver for positioning andLOS accuracy (e.g., open eGPS), magnetic compass for heading androtational information (e.g., gyroscopic), one or more accelerometersfor gestured input and tilt (achieves 3D positional algorithms, assuminggyroscopic compass).

As described earlier, a device can also include methods/interfaces tomake REST calls via GPRS/Wi-Fi and a file system and storage for storingand retrieving the application data and settings.

A device can also include user input and methods to map input to thevirtual keys. For instance, one non-limiting way to accomplish userinput is to have softkeys as follows, though it is to be understood agreat variety of user inputs can be used to achieve interaction with theuser interfaces of the pointing based services.

  SK up/down: //Up and down on choices   SK right, SK ok/confirm://Choose an option or drill down/next page   SK left, SK cancel/back,//Go back to a previous window, cancel   Exit / Incoming Call events//Exit the app or minimize

In addition, a representative device can include a graphics andwindowing stack to render the client side UI, as well as an audio stackto play sounds/alerts.

As mentioned, such a device may also include spatial and mathcomputational components including a set of APIs to perform 3D collisiontesting between subdivided surfaces such as spherical shells (e.g., asimple hit testing model to adopt and boundary definitions for POs),rotate points, and cull as appropriate from conic sections.

As described in various embodiments herein, FIGS. 34 and 35 illustratetwo processes for a device when location (e.g., GPS) and direction(e.g., compass) events occur. In FIG. 34, upon the occurrence of alocation or direction event, at 3400, it is determined whetherpredictive caching should be initiated for a next region to which a useris travelling. At 3410, if so, then the next region of data can bepre-fetched. At 3420, old regional data no longer of relevance can beaged out. At 3430, any usage data can be uploaded to the serviceframework for business intelligence, input to an advertisement engine,etc.

FIG. 35 represents another process for filtering potential POIs after apointing event. Upon the detection of a location and direction event, at3500, for POIs in the device's local cache, a group of POIs aredetermined that pass an intersection algorithm for the direction ofpointing of the device. At 3510, POIs in the group can be represented insome fashion on a UI, e.g., full view if only 1 POI, categorized view,2-D map view, 3-D perspective view, or user images if other users, etc.The possibilities for representation are limitless; the embodimentsdescribed herein are intuitive based on the general notion of pointingbased direction services.

At 3520, upon selection of a POI, static content is determined and anydynamic content is acquired via synchronization. When new data becomesavailable, it is downloaded to stay up to date. At 3530, POI informationis filtered further by user specific information (e.g., if it is theuser's first time at the store, returning customer, loyalty programmember, live baseball game offer for team clothing discounts, etc.). At3540, static and dynamic content that is up to date is rendered for thePOI. In addition, updates and/or interaction with POI information isallowed which can be synced back to the service.

Exemplary Networked and Distributed Environments

One of ordinary skill in the art can appreciate that the variousembodiments of methods and devices for pointing based services andrelated embodiments described herein can be implemented in connectionwith any computer or other client or server device, which can bedeployed as part of a computer network or in a distributed computingenvironment, and can be connected to any kind of data store. In thisregard, the various embodiments described herein can be implemented inany computer system or environment having any number of memory orstorage units, and any number of applications and processes occurringacross any number of storage units. This includes, but is not limitedto, an environment with server computers and client computers deployedin a network environment or a distributed computing environment, havingremote or local storage.

FIG. 36 provides a non-limiting schematic diagram of an exemplarynetworked or distributed computing environment. The distributedcomputing environment comprises computing objects 3610, 3612, etc. andcomputing objects or devices 3620, 3622, 3624, 3626, 3628, etc., whichmay include programs, methods, data stores, programmable logic, etc., asrepresented by applications 3630, 3632, 3634, 3636, 3638. It can beappreciated that objects 3610, 3612, etc. and computing objects ordevices 3620, 3622, 3624, 3626, 3628, etc. may comprise differentdevices, such as PDAs, audio/video devices, mobile phones, MP3 players,laptops, etc.

Each object 3610, 3612, etc. and computing objects or devices 3620,3622, 3624, 3626, 3628, etc. can communicate with one or more otherobjects 3610, 3612, etc. and computing objects or devices 3620, 3622,3624, 3626, 3628, etc. by way of the communications network 3640, eitherdirectly or indirectly. Even though illustrated as a single element inFIG. 36, network 3640 may comprise other computing objects and computingdevices that provide services to the system of FIG. 36, and/or mayrepresent multiple interconnected networks, which are not shown. Eachobject 3610, 3612, etc. or 3620, 3622, 3624, 3626, 3628, etc. can alsocontain an application, such as applications 3630, 3632, 3634, 3636,3638, that might make use of an API, or other object, software, firmwareand/or hardware, suitable for communication with or implementation ofthe delayed interaction model as provided in accordance with variousembodiments.

There are a variety of systems, components, and network configurationsthat support distributed computing environments. For example, computingsystems can be connected together by wired or wireless systems, by localnetworks or widely distributed networks. Currently, many networks arecoupled to the Internet, which provides an infrastructure for widelydistributed computing and encompasses many different networks, thoughany network infrastructure can be used for exemplary communications madeincident to the techniques as described in various embodiments.

Thus, a host of network topologies and network infrastructures, such asclient/server, peer-to-peer, or hybrid architectures, can be utilized.In a client/server architecture, particularly a networked system, aclient is usually a computer that accesses shared network resourcesprovided by another computer, e.g., a server. In the illustration ofFIG. 36, as a non-limiting example, computers 3620, 3622, 3624, 3626,3628, etc. can be thought of as clients and computers 3610, 3612, etc.can be thought of as servers where servers 3610, 3612, etc. provide dataservices, such as receiving data from client computers 3620, 3622, 3624,3626, 3628, etc., storing of data, processing of data, transmitting datato client computers 3620, 3622, 3624, 3626, 3628, etc., although anycomputer can be considered a client, a server, or both, depending on thecircumstances. Any of these computing devices may be processing data, orrequesting services or tasks that may implicate the delayed interactionmodel and related techniques as described herein for one or moreembodiments.

A server is typically a remote computer system accessible over a remoteor local network, such as the Internet or wireless networkinfrastructures. The client process may be active in a first computersystem, and the server process may be active in a second computersystem, communicating with one another over a communications medium,thus providing distributed functionality and allowing multiple clientsto take advantage of the information-gathering capabilities of theserver. Any software objects utilized pursuant to the direction basedservices can be provided standalone, or distributed across multiplecomputing devices or objects.

In a network environment in which the communications network/bus 3640 isthe Internet, for example, the servers 3610, 3612, etc. can be Webservers with which the clients 3620, 3622, 3624, 3626, 3628, etc.communicate via any of a number of known protocols, such as thehypertext transfer protocol (HTTP). Servers 3610, 3612, etc. may alsoserve as clients 3620, 3622, 3624, 3626, 3628, etc., as may becharacteristic of a distributed computing environment.

Exemplary Computing Device

As mentioned, various embodiments described herein apply to any devicewherein it may be desirable to perform pointing based services, anddelay interactions with points of interest. It should be understood,therefore, that handheld, portable and other computing devices andcomputing objects of all kinds are contemplated for use in connectionwith the various embodiments described herein, i.e., anywhere that adevice may request pointing based services. Accordingly, the belowgeneral purpose remote computer described below in FIG. 26 is but oneexample, and the embodiments of the subject disclosure may beimplemented with any client having network/bus interoperability andinteraction.

Although not required, any of the embodiments can partly be implementedvia an operating system, for use by a developer of services for a deviceor object, and/or included within application software that operates inconnection with the operable component(s). Software may be described inthe general context of computer-executable instructions, such as programmodules, being executed by one or more computers, such as clientworkstations, servers or other devices. Those skilled in the art willappreciate that network interactions may be practiced with a variety ofcomputer system configurations and protocols.

FIG. 37 thus illustrates an example of a suitable computing systemenvironment 3700 in which one or more of the embodiments may beimplemented, although as made clear above, the computing systemenvironment 3700 is only one example of a suitable computing environmentand is not intended to suggest any limitation as to the scope of use orfunctionality of any of the embodiments. Neither should the computingenvironment 3700 be interpreted as having any dependency or requirementrelating to any one or combination of components illustrated in theexemplary operating environment 3700.

With reference to FIG. 37, an exemplary remote device for implementingone or more embodiments herein can include a general purpose computingdevice in the form of a handheld computer 3710. Components of handheldcomputer 3710 may include, but are not limited to, a processing unit3720, a system memory 3730, and a system bus 3721 that couples varioussystem components including the system memory to the processing unit3720.

Computer 3710 typically includes a variety of computer readable mediaand can be any available media that can be accessed by computer 3710.The system memory 3730 may include computer storage media in the form ofvolatile and/or nonvolatile memory such as read only memory (ROM) and/orrandom access memory (RAM). By way of example, and not limitation,memory 3730 may also include an operating system, application programs,other program modules, and program data.

A user may enter commands and information into the computer 3710 throughinput devices 3740 A monitor or other type of display device is alsoconnected to the system bus 3721 via an interface, such as outputinterface 3750. In addition to a monitor, computers may also includeother peripheral output devices such as speakers and a printer, whichmay be connected through output interface 3750.

The computer 3710 may operate in a networked or distributed environmentusing logical connections to one or more other remote computers, such asremote computer 3770. The remote computer 3770 may be a personalcomputer, a server, a router, a network PC, a peer device or othercommon network node, or any other remote media consumption ortransmission device, and may include any or all of the elementsdescribed above relative to the computer 3710. The logical connectionsdepicted in FIG. 37 include a network 3771, such local area network(LAN) or a wide area network (WAN), but may also include othernetworks/buses. Such networking environments are commonplace in homes,offices, enterprise-wide computer networks, intranets and the Internet.

As mentioned above, while exemplary embodiments have been described inconnection with various computing devices, networks and advertisingarchitectures, the underlying concepts may be applied to any networksystem and any computing device or system in which it is desirable toderive information about surrounding points of interest.

There are multiple ways of implementing one or more of the embodimentsdescribed herein, e.g., an appropriate API, tool kit, driver code,operating system, control, standalone or downloadable software object,etc. which enables applications and services to use the pointing basedservices. Embodiments may be contemplated from the standpoint of an API(or other software object), as well as from a software or hardwareobject that provides pointing platform services in accordance with oneor more of the described embodiments. Various implementations andembodiments described herein may have aspects that are wholly inhardware, partly in hardware and partly in software, as well as insoftware.

The word “exemplary” is used herein to mean serving as an example,instance, or illustration. For the avoidance of doubt, the subjectmatter disclosed herein is not limited by such examples. In addition,any aspect or design described herein as “exemplary” is not necessarilyto be construed as preferred or advantageous over other aspects ordesigns, nor is it meant to preclude equivalent exemplary structures andtechniques known to those of ordinary skill in the art. Furthermore, tothe extent that the terms “includes,” “has,” “contains,” and othersimilar words are used in either the detailed description or the claims,for the avoidance of doubt, such terms are intended to be inclusive in amanner similar to the term “comprising” as an open transition wordwithout precluding any additional or other elements.

As mentioned, the various techniques described herein may be implementedin connection with hardware or software or, where appropriate, with acombination of both. As used herein, the terms “component,” “system” andthe like are likewise intended to refer to a computer-related entity,either hardware, a combination of hardware and software, software, orsoftware in execution. For example, a component may be, but is notlimited to being, a process running on a processor, a processor, anobject, an executable, a thread of execution, a program, and/or acomputer. By way of illustration, both an application running oncomputer and the computer can be a component. One or more components mayreside within a process and/or thread of execution and a component maybe localized on one computer and/or distributed between two or morecomputers.

The aforementioned systems have been described with respect tointeraction between several components. It can be appreciated that suchsystems and components can include those components or specifiedsub-components, some of the specified components or sub-components,and/or additional components, and according to various permutations andcombinations of the foregoing. Sub-components can also be implemented ascomponents communicatively coupled to other components rather thanincluded within parent components (hierarchical). Additionally, itshould be noted that one or more components may be combined into asingle component providing aggregate functionality or divided intoseveral separate sub-components, and any one or more middle layers, suchas a management layer, may be provided to communicatively couple to suchsub-components in order to provide integrated functionality. Anycomponents described herein may also interact with one or more othercomponents not specifically described herein but generally known bythose of skill in the art.

Furthermore, the claimed subject matter may be implemented as a method,apparatus, or article of manufacture using standard programming and/orengineering techniques to produce software, firmware, hardware, or anycombination thereof to control a computer to implement the disclosedsubject matter. The term “article of manufacture” as used herein isintended to encompass a computer program accessible from anycomputer-readable device, carrier, or media. For example, computerreadable media can include but are not limited to magnetic storagedevices (e.g., hard disk, floppy disk, magnetic strips . . . ), opticaldisks (e.g., compact disk (CD), digital versatile disk (DVD) . . . ),smart cards, and flash memory devices (e.g., card, stick, key drive . .. ). Additionally it should be appreciated that a carrier wave can beemployed to carry computer-readable electronic data such as those usedin transmitting and receiving electronic mail or in accessing a networksuch as the Internet or a local area network (LAN). Of course, thoseskilled in the art will recognize many modifications may be made to thisconfiguration without departing from the scope or spirit of the claimedsubject matter.

As used herein, the terms “infer” or “inference” generally refer to theprocess of reasoning about or inferring states of the system,environment, and/or user from a set of observations as captured viaevents and/or data. Inference can be employed to identify a specificcontext or action, or can generate a probability distribution overstates, for example. The inference can be probabilistic—that is, thecomputation of a probability distribution over states of interest basedon a consideration of data and events. Inference can also refer totechniques employed for composing higher-level events from a set ofevents and/or data. Such inference results in the construction of newevents or actions from a set of observed events and/or stored eventdata, whether or not the events are correlated in close temporalproximity, and whether the events and data come from one or severalevent and data sources.

In view of the exemplary systems described supra, methodologies that maybe implemented in accordance with the disclosed subject matter will bebetter appreciated with reference to the flowcharts of the variousfigures. While for purposes of simplicity of explanation, themethodologies are shown and described as a series of blocks, it is to beunderstood and appreciated that the claimed subject matter is notlimited by the order of the blocks, as some blocks may occur indifferent orders and/or concurrently with other blocks from what isdepicted and described herein. Where non-sequential, or branched, flowis illustrated via flowchart, it can be appreciated that various otherbranches, flow paths, and orders of the blocks, may be implemented whichachieve the same or a similar result. Moreover, not all illustratedblocks may be required to implement the methodologies describedhereinafter.

While the various embodiments have been described in connection with thepreferred embodiments of the various figures, it is to be understoodthat other similar embodiments may be used or modifications andadditions may be made to the described embodiment for performing thesame function without deviating therefrom. Still further, one or moreaspects of the above described embodiments may be implemented in oracross a plurality of processing chips or devices, and storage maysimilarly be effected across a plurality of devices. Therefore, thepresent invention should not be limited to any single embodiment, butrather should be construed in breadth and scope in accordance with theappended claims.

1. A portable electronic device, comprising: a memory that stores atleast information related to at least direction information representinginformation pertaining to orientation of the device, positioninformation representing information pertaining to location of thedevice and point of interest information representing informationpertaining to points of interest substantially within interactive rangeof the device; a positional component for receiving the positioninformation as a function of a location of the portable electronicdevice; a directional component that measures the direction informationas a function of an orientation of the portable electronic device; and atransmission component that transmits device data regarding interactionwith points of interest by the portable electronic device to at leastone remote device for aggregation of data regarding interaction with atleast some of the points of interest from a set of peer devices of amesh network.
 2. The device of claim 1, wherein the device isprovisioned with a set of direction based services tailored to thedevice based on an analysis of the aggregated data by the at least oneremote device.
 3. The system of claim 1, wherein the transmissioncomponent transmits device data including any one or more of useractivity, state, or context within the mesh network.
 4. The device ofclaim 1, further comprising: at least one processor configured toprocess the position information and the direction information todetermine at least one identifier of at least one point of interestsubstantially within interactive proximity of the device, to receiveinformation corresponding to the at least one identifier of the at leastone point of interest, and to display information if the deviceinteracts with the at least one point of interest with the device.
 5. Amethod for provisioning direction based services, comprising: inferringor determining a device has entered into a mesh network of cooperatingdevices; inferring or determining goals of the device; mapping the goalsto a set of direction based services, which are based at least partly ondevice orientation, available within the mesh network; and provisioninga subset of the direction based services to the device.
 6. The method ofclaim 5, wherein the mapping act comprises mapping based on at least oneof: user demographics, user state, user context, user preferences, oravailable resources.
 7. The method of claim 5 further comprising:identifying a set of direction based services that are not provisionedto the device.
 8. The method of claim 5, further comprising: refining aknowledge base or data model utilized in connection with direction basedservices provisioning based on results relating to the provisioning ofdirection based services.
 9. The method of claim 5, wherein theprovisioning includes provisioning the device with at least one targetedadvertisement.
 10. The method of claim 5, further comprising: analyzingactivity regarding a plurality of devices within the mesh network, andbased on the analyzing, tailoring the provisioning of direction basedservices in real-time or future.
 11. The method of claim 5, furthercomprising: analyzing activity regarding a plurality of devices withinthe mesh network, and based on the analyzing, determining at least oneof: user traffic, wait time for service, resource availability, or userdensity.
 12. A mesh-network based host computer system for provisioningservices, comprising: at least one storage device that stores a datamodel that facilitates provisioning of services within a mesh network,the data model employs aggregated and processed data relating to prioruser or device interactions within the mesh network; a monitor componentthat receives data regarding user or device interaction within the meshnetwork; an analysis component that analyzes the received data, andinfers or determines a user or device goal; and a provisioning componentthat employs the data model and results of the data analyses to identifyand provision a set of pointing based services to the user or devicewithin the mesh network.
 13. The system of claim 12, the analysiscomponent factors as part of the analyses at least one of: userdemographics, user state, user context, user preferences, or availableresources.
 14. The system of claim 13, wherein the provisioningcomponent provisions targeted advertisements to the user or device. 15.The system of claim 13, wherein as part of the analyses the analysiscomponent infers or determines level of user traffic at a store, andwait time to completion of a commercial transaction, and theprovisioning component recommends another store as a function of theanalyses.
 16. The system of claim 15, wherein the analysis componentfactors user goals, and time constraints as part of the analysis. 17.The system of claim 13, wherein the provisioning component orders itemsto be provisioned to the user or device based on a pre-defined orderingalgorithm.
 18. The system of claim 17, wherein the provisioningcomponent employs a utility-based analysis in connection with orderingand provisioning of pointing based services.
 19. The system of claim 13,wherein results of provisioning of pointing based services is employedto train the data model.
 20. The system of claim 13, wherein the datamodel can adaptively interact with other data models.